Clinical and biochemical characteristics of children with juvenile idiopathic arthritis.
Bibliographic record
Abstract
OBJECTIVE: To determine the clinical and biochemical characteristics of children with Juvenile Idiopathic Arthritis (JIA) at a tertiary care centre in Karachi, Pakistan. STUDY DESIGN: A descriptive study. PLACE AND DURATION OF STUDY: Paediatric Rheumatology Clinic of The Aga Khan University Hospital (AKUH), Karachi, from January 2008 to December 2011. METHODOLOGY: Clinical and laboratory profile and outcome of children less than 15 years of age attending the Paediatric Rheumatology Clinic of the Aga Khan University, Karachi with the diagnosis of Juvenile Idiopathic Arthritis according to International League against Rheumatism were studied. These children were classified into different types of JIA; their clinical and laboratory characteristics, response to therapy and outcome was evaluated. RESULTS: Sixty eight patients satisfying the criteria of International League against Rheumatism (ILAR) for Juvenile Idiopathic Arthritis were enrolled during the study period of four consecutive years, their age ranged from 9 months to 15 years. Mean age at onset was 6.45 ± 4.03 years while mean age at diagnosis was 7.60 ± 3.93 years. Polyarticular was the most predominant subtype with 37 (54%) patients, out of these, 9 (24%) were rheumatoid factor positive. An almost equal gender predisposition was observed. Fever and arthritis were the most common presenting symptoms, with only 2 patients presenting with uveitis. CONCLUSION: The clinico-biochemical characteristics of JIA at the study centre showed a pattern distinct with early onset of disease, high frequency of polyarticular type and a higher rheumatoid factor (QRA) and ANA positivity in girls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".